基于BP神经网络的铁路货运安全风险评价研究

Research on railway freight safety risk assessment based on BP neural network

铁路货运安全是铁路货运质量的核心内容,现今铁路货物列车运行速度大幅提高,铁路货运产品种类不断丰富、总量不断增加,铁路货运安全风险管理面临更大挑战。反向传播(BP)神经网络算法相较于常规算法具有收敛快、计算精确和弱化人为因素影响等优点。针对铁路货运安全中存在的风险,建立适当的评价指标体系,使用模糊算法、层次分析法(AHP)量化样本数据,降低数据主观性,通过建立BP神经网络模型,评价铁路货运安全风险;以丰台货运中心的各项数据为例进行验证,结果表明:基于BP神经网络的铁路货运安全风险评价模型能够保证预测结果的准确性。

Railway freight safety is the core content for railway freight quality. Currently,the speed of freight train has been greatly improved,the products transported have been enriched and the total amount of products has been increased,thus,the railway freight safety risk management facedmore challenges. BP nerve network algorithm has the advantages of rapid convergence,accurate calculation,and weakening the influence of human factors etc. a proper evaluation index system for risks was set up according to the potential dangers existing in railway freight safety. It quantified the sample data and reduced the data subjectivity by using the fuzzy algorithm and AHP methods,and carrying out the risk assessment and reached the corresponding conclusions via setting up BP neural network model. Taken various data of Fengtai Railway Freight Center as an example,the results show that the accuracy of predicting the result can be guaranteed by adopting the safety risk assessment model based on BP neural network.